Cover Image

Concept-Based Explainable Artificial Intelligence: Metrics and Benchmarks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aysel, Halil Ibrahim, Cai, Xiaohao, Prugel-Bennett, Adam
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Semantic Segmentation by Semantic Proportions
by: Aysel, Halil Ibrahim, et al.
Published: (2023)

RNNs, CNNs and Transformers in Human Action Recognition: A Survey and a Hybrid Model
by: Alomar, Khaled, et al.
Published: (2024)

Explainable Artificial Intelligence (XAI) for Internet of Things: A Survey
by: Kok, Ibrahim, et al.
Published: (2022)

CornerPoint3D: Look at the Nearest Corner Instead of the Center
by: Zhang, Ruixiao, et al.
Published: (2025)

Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review
by: Lopez-Ramos, Luis M., et al.
Published: (2024)

Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
by: Mikriukov, Georgii, et al.
Published: (2026)

A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
by: Salih, Ahmed, et al.
Published: (2023)

Explainable Artificial Intelligence and Multicollinearity : A Mini Review of Current Approaches
by: Salih, Ahmed M
Published: (2024)

Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspective
by: Xiong, Haoyi, et al.
Published: (2024)

Explainable Artificial Intelligence Techniques for Accurate Fault Detection and Diagnosis: A Review
by: Maged, Ahmed, et al.
Published: (2024)

Visual Analytics for Explainable and Trustworthy Artificial Intelligence
by: Chatzimparmpas, Angelos
Published: (2025)

A Diagnosis and Treatment of Liver Diseases: Integrating Batch Processing, Rule-Based Event Detection and Explainable Artificial Intelligence
by: Chandra, Ritesh, et al.
Published: (2023)

Breast Cancer Diagnosis: A Comprehensive Exploration of Explainable Artificial Intelligence (XAI) Techniques
by: Bai, Samita, et al.
Published: (2024)

Benchmarking Artificial Intelligence Models for Daily Coastal Hypoxia Forecasting
by: Rajasekaran, Magesh, et al.
Published: (2026)

Uncertainty Quantification as a Principled Foundation for Explainable Artificial Intelligence: A Case Study of Counterfactual Explanations
by: Sokol, Kacper, et al.
Published: (2025)

XAI-Units: Benchmarking Explainability Methods with Unit Tests
by: Lee, Jun Rui, et al.
Published: (2025)

Deeply Explainable Artificial Neural Network
by: Zucker, David
Published: (2025)

Can Requirements Engineering Support Explainable Artificial Intelligence? Towards a User-Centric Approach for Explainability Requirements
by: Umm-e-Habiba, et al.
Published: (2022)

SIDE: Sparse Information Disentanglement for Explainable Artificial Intelligence
by: Dubovik, Viktar, et al.
Published: (2025)

Explainable Artificial Intelligence Model for Evaluating Shear Strength Parameters of Municipal Solid Waste Across Diverse Compositional Profiles
by: Suknark, Parichat, et al.
Published: (2025)

Explainable Artificial Intelligent (XAI) for Predicting Asphalt Concrete Stiffness and Rutting Resistance: Integrating Bailey's Aggregate Gradation Method
by: Kongkitkul, Warat, et al.
Published: (2024)

Beyond Models! Explainable Data Valuation and Metric Adaption for Recommendation
by: Jia, Renqi, et al.
Published: (2025)

Probabilistic Artificial Intelligence
by: Krause, Andreas, et al.
Published: (2025)

A Survey on Explainable Reinforcement Learning: Concepts, Algorithms, Challenges
by: Qing, Yunpeng, et al.
Published: (2022)

Explainable Artificial Intelligence Techniques for Software Development Lifecycle: A Phase-specific Survey
by: Arora, Lakshit, et al.
Published: (2025)

Artificial Intelligence for CRISPR Guide RNA Design: Explainable Models and Off-Target Safety
by: Abbaszadeh, Alireza, et al.
Published: (2025)

Towards Transparent and Accurate Diabetes Prediction Using Machine Learning and Explainable Artificial Intelligence
by: Khokhar, Pir Bakhsh, et al.
Published: (2025)

Rethinking Deep Thinking: Stable Learning of Algorithms using Lipschitz Constraints
by: Bear, Jay, et al.
Published: (2024)

Artificial Neural Nets and the Representation of Human Concepts
by: Freiesleben, Timo
Published: (2023)

Evaluating Explainability in Machine Learning Predictions through Explainer-Agnostic Metrics
by: Munoz, Cristian, et al.
Published: (2023)

Explainable Human Activity Recognition: A Unified Review of Concepts and Mechanisms
by: Kundu, Mainak, et al.
Published: (2026)

Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication
by: Keenan, Bernard, et al.
Published: (2023)

ShaTS: A Shapley-based Explainability Method for Time Series Artificial Intelligence Models applied to Anomaly Detection in Industrial Internet of Things
by: de la Peña, Manuel Franco, et al.
Published: (2025)

Explainable Molecular Property Prediction: Aligning Chemical Concepts with Predictions via Language Models
by: Wang, Zhenzhong, et al.
Published: (2024)

Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction
by: Mersha, Melkamu, et al.
Published: (2024)

Measuring Cross-Modal Synergy: A Benchmark for VLM Explainability
by: Ky, Joël Roman, et al.
Published: (2026)

SpectrumWorld: Artificial Intelligence Foundation for Spectroscopy
by: Yang, Zhuo, et al.
Published: (2025)

Causal Bias Detection in Generative Artificial Intelligence
by: Plecko, Drago
Published: (2026)

Open-Endedness is Essential for Artificial Superhuman Intelligence
by: Hughes, Edward, et al.
Published: (2024)

TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets
by: Chen, Jintai, et al.
Published: (2024)